25:["$","title",null,{"children":"Data wrangling essentials: comparisons in JavaScript, Python, SQL, R, and Excel | Serdar Balcı | Observable"}] 49:T453,salesData = [ { //id: 1, date: "2022-01-01", product: "Product A", description: "Shirt - small", //category: "Category 1", unitsSold: 10, unitPrice: 50, totalRevenue: 500, region: "North" }, { //id: 2, date: "2022-01-02", product: "Product B", description: "Sweatshirt - large", //category: "Category 2", unitsSold: 15, unitPrice: 25, totalRevenue: 375, region: "South" }, { //id: 3, date: "2022-01-03", product: "Product C", description: "Jacket - small", //category: "Category 1", unitsSold: 8, unitPrice: 75, totalRevenue: 600, region: "West" }, { //id: 4, date: "2022-01-04", product: "Product A", description: "Shirt - medium", //category: "Category 2", unitsSold: 5, unitPrice: 100, totalRevenue: 500, region: "East" }, { //id: 5, date: "2022-01-05", product: "Product B", description: "Sweatshirt - large", //category: "Category 1", unitsSold: 20, unitPrice: 30, totalRevenue: 600, region: "North" }]4a:T2cb0,compareFunctions = [ { method: "Filter rows", language: "JavaScript", function: "Array filter", link: "https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Global_Objects/Array/filter", example: '`salesData.filter(d => d.region === "West")`' }, { method: "Filter rows", language: "Python", function: "pandas query", link: "https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.query.html", example: "`salesData.query('region==\"West\"')`" }, { method: "Filter rows", language: "SQL", function: "WHERE", link: "https://www.w3schools.com/sql/sql_where.asp", example: "`SELECT * FROM salesData WHERE region=\'West\'`" }, {method: "Filter rows", language: "R", function: "dplyr filter", link: "https://dplyr.tidyverse.org/reference/filter.html", example: "`salesData` |`>` `filter(region == \"West\")`" }, { method: "Filter rows", language: 'Excel', function: 'FILTER', link: "https://support.microsoft.com/en-us/office/filter-function-f4f7cb66-82eb-4767-8f7c-4877ad80c759", example: '`=FILTER(A2:H12, H2:H12="West")`' }, { method: "Select columns", language: "JavaScript", function: "Array map", link: "https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Global_Objects/Array/map", example: "`salesData.map(d => ({ date: d.date, product: d.product, totalRevenue: d.totalRevenue }))`" }, { method: "Select columns", language: "Python", function: "brackets [[]]", link: "https://pandas.pydata.org/docs/getting_started/intro_tutorials/03_subset_data.html", example: "`salesData[['date', 'product', 'totalRevenue']]`" }, { method: "Select columns", language: "SQL", function: "SELECT", link: "https://www.w3schools.com/sql/sql_select.asp", example: " `SELECT date, product, totalRevenue FROM salesData`" }, { method: "Select columns", language: "R", function: "dplyr select", link: "https://dplyr.tidyverse.org/reference/select.html", example: "`salesData` |`>` `select(date, product, totalRevenue)`" }, { method: "Select columns", language: 'Excel', function: 'CHOOSECOLS', link: 'https://support.microsoft.com/en-gb/office/choosecols-function-bf117976-2722-4466-9b9a-1c01ed9aebff', example: '`=CHOOSECOLS(A1:H12, 1, 2, 6)` _(date, product and totalRevenue are columns 1, 2 and 6 in range)_' }, { method: "Group by variable", language: 'JavaScript', function: 'd3.rollup', link: 'https://github.com/d3/d3-array/blob/main/README.md#rollup', example: '`d3.rollup(salesData, v => d3.sum(v, d => d.totalRevenue), d => d.region)`' }, { method: "Group by variable", language: 'Python', function: 'pandas groupby', link: 'https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.groupby.html', example: '`salesData.groupby(\'region\')[\'totalRevenue\'].sum()`' }, { method: "Group by variable", language: 'SQL', function: 'GROUP BY', link: 'https://www.w3schools.com/sql/sql_groupby.asp', example: '`SELECT region, SUM(totalRevenue) AS regionRevenue FROM salesData GROUP BY region`' }, { method: "Group by variable", language: 'R', function: 'dplyr group_by', link: 'https://dplyr.tidyverse.org/reference/group_by.html', example: '`salesData` |`>` `group_by(region)` |`>` `summarize(regionRevenue = sum(totalRevenue))`' }, { method: "Group by variable", language: 'Excel', function: 'pivot table', link: 'https://support.microsoft.com/en-us/office/create-a-pivottable-to-analyze-worksheet-data-a9a84538-bfe9-40a9-a8e9-f99134456576', example: '_(Insert > PivotTable)_' }, { method: "Add a column", language: 'JavaScript', function: 'Array map', link: 'https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Global_Objects/Array/map', example: '`salesData.map(d => ({...d, discountedPrice: 0.9 * d.unitPrice }))`' }, { method: "Add a column", language: 'Python', function: 'brackets []', link: 'https://pandas.pydata.org/docs/getting_started/intro_tutorials/05_add_columns.html', example: '`salesData[\'discountedPrice\'] = 0.9 * salesData[\'unitPrice\']`' }, { method: "Add a column", language: 'SQL', function: 'AS', link: 'https://www.w3schools.com/sql/sql_ref_as.asp', example: '`SELECT *, unitPrice * .9 AS discountedPrice FROM salesData`' }, { method: "Add a column", language: 'R', function: 'dplyr mutate', link: 'https://dplyr.tidyverse.org/reference/mutate.html', example: '`salesData` |`>` `mutate(discountedPrice = 0.9 * unitPrice)`' }, { method: "Add a column", language: 'Excel', function: 'add in spreadsheet', link: 'https://support.microsoft.com/en-us/office/use-calculated-columns-in-an-excel-table-873fbac6-7110-4300-8f6f-aafa2ea11ce8', example: '`= F2 * 0.9`' }, { method: "Sort data", language: 'JavaScript', function: 'Array sort', link: 'https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Global_Objects/Array/sort', example: '`salesData.sort((a, b) => a.totalRevenue - b.totalRevenue)`' }, { method: "Sort data", language: 'Python', function: 'pandas sort_values', link: 'https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.sort_values.html', example: '`salesData.sort_values(by=[\'totalRevenue\'])`' }, { method: "Sort data", language: 'SQL', function: 'ORDER BY', link: 'https://www.w3schools.com/sql/sql_orderby.asp', example: '`SELECT * FROM salesData ORDER BY totalRevenue`' }, { method: "Sort data", language: 'R', function: 'dplyr arrange', link: 'https://dplyr.tidyverse.org/reference/arrange.html', example: '`salesData` |`>` `arrange(totalRevenue)`' }, { method: "Sort data", language: 'Excel', function: 'SORT', link: 'https://support.microsoft.com/en-us/office/sort-function-22f63bd0-ccc8-492f-953d-c20e8e44b86c', example: '`=SORT(A2:H12, 6)` _(totalRevenue is column 6 in range)_' }, { method: "Rename a column", language: 'JavaScript', function: 'Array map', link: 'https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Global_Objects/Array/map', example: '`salesData.map(d => ({...d, saleDate: d.date }))`' }, { method: "Rename a column", language: 'Python', function: 'pandas rename', link: 'https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.rename.html', example: '`salesData.rename(columns={"date": "saleDate"})`' }, { method: "Rename a column", language: 'SQL', function: 'SELECT AS', link: 'https://www.w3schools.com/sql/sql_ref_as.asp', example: '`SELECT *, date AS saleDate FROM salesData`' }, { method: "Rename a column", language: 'R', function: 'dplyr rename', link: 'https://dplyr.tidyverse.org/reference/rename.html', example: '`salesData` |`>` `rename(saleDate = date)`' }, { method: "Rename a column", language: 'Excel', function: 'update manually', link: 'https://support.microsoft.com/en-us/office/edit-cell-contents-9c8489f6-08c4-4932-a6bc-4de0a8cf86d6', example: '_(click in cell, type new name)_' }, { method: "Access a value", language: 'JavaScript', function: 'Array map', link: 'https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Global_Objects/Array', example: '`salesData.map(d => d.description)[3]`' }, { method: "Access a value", language: 'Python', function: 'loc, iloc', link: 'https://pandas.pydata.org/docs/user_guide/indexing.html', example: '`salesData.iloc[[3], [2]]`' }, { method: "Access a value", language: 'SQL', function: 'SELECT + LIMIT + OFFSET', link: 'https://www.w3schools.com/php/php_mysql_select_limit.asp', example: '`SELECT description FROM salesData LIMIT 1 OFFSET 3`' }, { method: "Access a value", language: 'R', function: '$ []', link: 'http://www.cookbook-r.com/Basics/Indexing_into_a_data_structure/', example: '`salesData$description[4]`' }, { method: "Access a value", language: 'Excel', function: 'A1 notation', link: 'https://learn.microsoft.com/en-us/office/vba/excel/concepts/cells-and-ranges/refer-to-cells-and-ranges-by-using-a1-notation', example: '`= C4`' }, { method: "Merge columns", language: 'JavaScript', function: 'Array map', link: 'https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Global_Objects/Array/map', example: '`salesData.map(d => ({...d, fullDescription:` `` `${d.product} ${d.description}` ``}))`' }, { method: "Merge columns", language: 'Python', function: '+ (concatenation)', link: 'https://www.w3schools.com/python/gloss_python_string_concatenation.asp', example: '`salesData[\'fullDescription\'] = salesData\[\'product\'\] + \' \' + salesData\[\'description\'\]`' }, { method: "Merge columns", language: 'SQL', function: 'CONCAT', link: 'https://learn.microsoft.com/en-us/sql/t-sql/functions/concat-transact-sql?view=sql-server-ver16', example: '`SELECT *, CONCAT(product, \' \', description) AS fullDescription from salesData`' }, { method: "Merge columns", language: 'R', function: 'tidyr unite', link: 'https://tidyr.tidyverse.org/reference/unite.html', example: '`salesData` |`>` `unite("fullDescription", c(product, description), sep = " ")`' }, { method: "Merge columns", language: 'Excel', function: '& or CONCAT', link: 'https://support.microsoft.com/en-us/office/combine-text-from-two-or-more-cells-into-one-cell-81ba0946-ce78-42ed-b3c3-21340eb164a6', example: '`=CONCAT(B2," ", C2)`' }, { method: "Join", language: 'JavaScript', function: 'Arquero join_left', link: 'https://uwdata.github.io/arquero/api/verbs#join_left', example: '`salesData.join_left(productDetails, [\'product\', \'product_id\'])` _(if salesData is an Arquero table)_' }, { method: "Join", language: 'Python', function: 'pandas merge', link: 'https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.merge.html', example: '`salesData.merge(productDetails, left_on=\'product\', right_on=\'product_id\', how=\'left\')`' }, { method: "Join", language: 'SQL', function: 'LEFT JOIN', link: 'https://www.w3schools.com/sql/sql_join.asp', example: '`SELECT * FROM salesData JOIN productDetails ON salesData.product = productDetails.product_id`' }, { method: "Join", language: 'R', function: 'dplyr left_join', link: 'https://dplyr.tidyverse.org/reference/mutate-joins.html', example: '`salesData` |`>` `left_join(productDetails, by = c("product" = "product_id"))`' }, { method: "Join", language: 'Excel', function: 'Power Query merge', link: 'https://learn.microsoft.com/en-us/power-query/merge-queries-left-outer', example: '*(merge query)*' } ]4b:T951,async function imageInput({ value = ["JavaScript", "Python", "SQL", "R", "Excel"] } = {}) { const output = htl.html``; const node = htl.html`

Click on the icons to include or exclude languages in the tables below:

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Here, we show common data wrangling methods (like filtering, sorting, and adding columns) in JavaScript, Python, SQL, R, and Excel. All examples use the mock data below, stored as _salesData_:","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":827,"value":"salesData","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":919,"value":"---\n## Comparison tables\nThe comparison tables below are not comprehensive; many good (in some cases, better) alternatives exist in each language, and we do not cover myriad caveats (e.g. handling missing values). In general, we use tidyverse functions for R examples and pandas functions for Python examples.","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":536,"value":"viewof langCheckbox = imageInput()","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":2273,"value":"---\n${await FileAttachment(\"filter-sml.png\").image({width: 120, align: \"right\"})}\n### Filter rows\nKeep rows for the West _region_ in _salesData_.","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":1142,"value":"$${comparisonTable(filteredFunctions.filter(d => d.method == \"Filter rows\"))}","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":2272,"value":"---\n${await FileAttachment(\"select-sm.png\").image({width: 120, align: \"right\"})}\n### Select columns\nCreate a subset of _salesData_ containing only _date_, _product_, and _totalRevenue_.","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":1153,"value":"$${comparisonTable(filteredFunctions.filter(d => d.method == \"Select columns\"))}","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":2271,"value":"---\n${await FileAttachment(\"sort-sm.png\").image({width: 120, align: \"right\"})}\n### Sort data\nReorder _salesData_ by _totalRevenue_ (low to high).","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":1286,"value":"$${comparisonTable(filteredFunctions.filter(d => d.method == \"Sort data\"))}","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":2270,"value":"---\n${await FileAttachment(\"add-column-sm.png\").image({width: 120, align: \"right\"})}\n### Add a new column\nAdd a new column to _salesData_ with a _discountedPrice_, which takes 10% off each _unitPrice_.","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":1259,"value":"$${comparisonTable(filteredFunctions.filter(d => d.method == \"Add a column\"))}","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":2269,"value":"---\n${await FileAttachment(\"group-summarize-sm.png\").image({width: 120, align: \"right\"})}\n### Operations by group\nReturn the sum of _totalRevenue_ for each _region_ in _salesData_.","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":1251,"value":"$${comparisonTable(filteredFunctions.filter(d => d.method == \"Group by variable\"))}","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":1349,"value":"---\n${await FileAttachment(\"rename-sm.png\").image({width: 120, align: \"right\"})}\n### Rename a column\nStore a version of the _date_ with new name _saleDate_, while keeping all other columns. The JavaScript and SQL code below adds a new column called _saleDate_. The Python and R code rename the existing _date_ column as _saleDate_","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":1354,"value":"$${comparisonTable(filteredFunctions.filter(d => d.method == \"Rename a column\"))}","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":2267,"value":"---\n${await FileAttachment(\"index-array.png\").image({width: 120, align: \"right\"})}\n### Access a value\nAccess the fourth value from the _description_ property in _salesData_.","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":1385,"value":"$${comparisonTable(filteredFunctions.filter(d => d.method == \"Access a value\"))}","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":2266,"value":"---\n${await FileAttachment(\"unite-sm.png\").image({width: 120, align: \"right\"})}\n### Merge values from two columns into one\nUnite the _product_ and _description_ columns into a single column called _fullDescription_, using a comma as a separator.","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":1490,"value":"$${comparisonTable(filteredFunctions.filter(d => d.method == \"Merge columns\"))}","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":1530,"value":"---\n${await FileAttachment(\"join-sm.png\").image({width: 120, align: \"right\"})}\n### Join tables\nUse a left join to join information from a _productDetails_ table to _salesData_. Join on _product_ in _salesData_ and *product_id* in _productDetails_ .","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":1542,"value":"$${comparisonTable(filteredFunctions.filter(d => d.method == \"Join\"))}","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":925,"value":"

\n---\n## Appendix","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":1302,"value":"_Table template and styling:_","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":487,"value":"comparisonTable = (contents) => {\n\n const groupedResults = d3.flatGroup(contents, d => d.method);\n \n let returnMD = ``;\n\n groupedResults.forEach(thisGroup => {\n \n returnMD += `| Language | Method | Example |\n | :-- | :-- | :--\n `\n\n thisGroup[1].forEach(doc => {\n returnMD += `| ${doc.language}`\n returnMD += `| ${doc.function} `\n returnMD += `| ${doc.example} |\n `\n })\n \n returnMD += `\n`\n })\n \n \n \n return returnMD\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":522,"value":"","pinned":false,"hidden":false,"mode":"html","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":970,"value":"_salesData:_","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":34,"value":"$49","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":972,"value":"_Array with methods information: _","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":493,"value":"$4a","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":974,"value":"_Filtered version of above, based on inputs:_","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":542,"value":"filteredFunctions = compareFunctions.filter(d => langCheckbox.includes(d.language))","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":1714,"value":"Data used for join section: ","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":1713,"value":"productDetails = await FileAttachment(\"productDetails.csv\").csv({typed: \"auto\"})","pinned":true,"hidden":true,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"productDetails","database":"$undefined"},{"id":1947,"value":"import {set} from \"@tophtucker/custom-input-example\"","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":1975,"value":"$4b","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"}],"files":"$W4c","stdlib":"1"}} 24:null